Elasticsearch vs MonkeyLearn vs Swift AI Comparison | StackShare | StackShare

Elasticsearch vs MonkeyLearn vs Swift AI

Overview

Elasticsearch

Stacks35.0K

Followers27.1K

Votes1.6K

MonkeyLearn

Stacks16

Followers44

Votes2

Swift AI

Stacks14

Followers52

Votes0

Advice on Elasticsearch, MonkeyLearn, Swift AI

Rana Usman

Chief Technology Officer at TechAvanza

Jun 4, 2020

Needs adviceon

Firebase

Elasticsearch

Algolia

Hey everybody! (1) I am developing an android application. I have data of around 3 million record (less than a TB). I want to save that data in the cloud. Which company provides the best cloud database services that would suit my scenario? It should be secured, long term useable, and provide better services. I decided to use Firebase Realtime database. Should I stick with Firebase or are there any other companies that provide a better service?

(2) I have the functionality of searching data in my app. Same data (less than a TB). Which search solution should I use in this case? I found Elasticsearch and Algolia search. It should be secure and fast. If any other company provides better services than these, please feel free to suggest them.

Thank you!

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Comments

Detailed Comparison

Elasticsearch	MonkeyLearn	Swift AI
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).	Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.	Swift AI is a high-performance AI and machine learning library written entirely in Swift. We currently support iOS and OS X, with support for more platforms coming soon!
Distributed and Highly Available Search Engine;Multi Tenant with Multi Types;Various set of APIs including RESTful;Clients available in many languages including Java, Python, .NET, C#, Groovy, and more;Document oriented;Reliable, Asynchronous Write Behind for long term persistency;(Near) Real Time Search;Built on top of Apache Lucene;Per operation consistency;Inverted indices with finite state transducers for full-text querying;BKD trees for storing numeric and geo data;Column store for analytics;Compatible with Hadoop using the ES-Hadoop connector;Open Source under Apache 2 and Elastic License	Define your custom categories and tags to structure your text data. Process thousands of texts and get actionable insights. Implement NLP features in your product with our scalable API. We provide SDKs for major programming languages. No NLP or Machine Learning knowledge is required. Just play with our elegant UI and our Patent Pending Algorithm creation Engine.	Feed-Forward Neural Network; Fast Matrix Library
Statistics
Stacks 35.0K	Stacks 16	Stacks 14
Followers 27.1K	Followers 44	Followers 52
Votes 1.6K	Votes 2	Votes 0
Pros & Cons
Pros 329 Powerful api 315 Great search engine 231 Open source 214 Restful 200 Near real-time search Cons 7 Resource hungry 6 Diffecult to get started 5 Expensive 4 Hard to keep stable at large scale	Pros 2 Easy to use	No community feedback yet
Integrations
Kibana Beats Logstash	Zapier Mode Zendesk FreshDesk Front Delighted Google Sheets Looker	Swift

What are some alternatives to Elasticsearch, MonkeyLearn, Swift AI?

Algolia

Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Typesense

It is an open source, typo tolerant search engine that delivers fast and relevant results out-of-the-box. has been built from scratch to offer a delightful, out-of-the-box search experience. From instant search to autosuggest, to faceted search, it has got you covered.

Amazon CloudSearch

Amazon CloudSearch enables you to search large collections of data such as web pages, document files, forum posts, or product information. With a few clicks in the AWS Management Console, you can create a search domain, upload the data you want to make searchable to Amazon CloudSearch, and the search service automatically provisions the required technology resources and deploys a highly tuned search index.

rasa NLU

rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.

Amazon Elasticsearch Service

Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

Manticore Search

It is a full-text search engine written in C++ and a fork of Sphinx Search. It's designed to be simple to use, light and fast, while allowing advanced full-text searching. Connectivity is provided via a MySQL compatible protocol or HTTP, making it easy to integrate.